{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dd95c7c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import ticker\n",
    "import seaborn as sns\n",
    "from matplotlib.pyplot import MultipleLocator\n",
    "import matplotlib as mpl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d3e70b2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_picture(plt, file_type, title):\n",
    "    plt.savefig(title + '.' + file_type, bbox_inches='tight', format=file_type, dpi=300, transparent = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8ba44b9",
   "metadata": {},
   "source": [
    "# A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "11aeaff5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "x = np.arange(-5, 5, 0.0005)\n",
    "p_2 = []\n",
    "for t in x:\n",
    "    y = 1 +0*t -0.0384615*t**2\n",
    "    p_2.append(y)\n",
    "    \n",
    "p_4 = []\n",
    "for t in x:\n",
    "    y =1 +0*t -0.171088*t**2 +0*t**3 +0.00530504*t**4\n",
    "    p_4.append(y)\n",
    "    \n",
    "p_6 = []\n",
    "for t in x:\n",
    "    y =1 +2.77556e-17*t -0.351364*t**2 +0*t**3 +0.0335319*t**4 +8.67362e-19*t**5 -0.000840633*t**6\n",
    "    p_6.append(y)\n",
    "    \n",
    "p_8 = []\n",
    "for t in x:\n",
    "    y = 1 +2.77556e-17*t -0.528121*t**2 -6.93889e-17*t**3 +0.0981875*t**4 +0*t**5 -0.00658016*t**6 +0*t**7 +0.000137445*t**8\n",
    "    p_8.append(y)\n",
    "\n",
    "Y = []\n",
    "for t in x:\n",
    "    y = 1/(1+t*t)\n",
    "    Y.append(y)\n",
    "plt.figure(figsize=(6,4))\n",
    "plt.plot(x, p_2,\"r\",label=\"n=2\")\n",
    "plt.plot(x, p_4,\"y\",label=\"n=4\")\n",
    "plt.plot(x, p_6,\"g\",label=\"n=6\")\n",
    "plt.plot(x, p_8,\"b\",label=\"n=8\")\n",
    "plt.plot(x, Y,\"k:\",label=\"y\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.xlim(-5,5)\n",
    "plt.ylim(-1,1)\n",
    "plt.legend()\n",
    "plt.title(\"B\", fontsize=14,x=0.5,y=-0.25)\n",
    "save_picture(plt, \"png\", \"B\")\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2366d02",
   "metadata": {},
   "source": [
    "# B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "21c63c8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "x = np.arange(-1.2, 1, 0.0005)\n",
    "p_5 = []\n",
    "for t in x:\n",
    "    y = 0.444089 +1.76965e-16*t -1.09581*t**2 +2.9326e-16*t**3 +0.711567*t**4 -5.17224e-16*t**5\n",
    "    p_5.append(y)\n",
    "    \n",
    "p_10 = []\n",
    "for t in x:\n",
    "    y =1 +1.11022e-15*t -12.4765*t**2 -1.59872e-14*t**3 +61.443*t**4 +1.7053e-13*t**5 -133.445*t**6 -4.26326e-14*t**7 +130.106*t**8 +3.55271e-14*t**9 -46.6329*t**10\n",
    "    p_10.append(y)\n",
    "    \n",
    "p_15 = []\n",
    "for t in x:\n",
    "    y =0.916893 -1.86274e-15*t -12.2846*t**2 +1.04628e-13*t**3 +83.7238*t**4 +4.41453e-13*t**5 -305.961*t**6 +1.59502e-12*t**7 +628.141*t**8 -5.31667e-12*t**9 -725.649*t**10 +2.90526e-12*t**11 +440.077*t**12 -2.59524e-12*t**13 -108.93*t**14 +6.64002e-13*t**15\n",
    "    p_15.append(y)\n",
    "    \n",
    "p_20 = []\n",
    "for t in x:\n",
    "    y = 1 +4.16334e-16*t -21.7623*t**2 +1.95399e-14*t**3 +306.629*t**4 +5.68434e-13*t**5 -2537.27*t**6 +1.27329e-11*t**7 +12635.6*t**8 +9.27685e-11*t**9 -39333.3*t**10 +7.27596e-11*t**11 +78236.3*t**12 +4.00178e-10*t**13 -99300.1*t**14 +5.31145e-10*t**15 +77754.5*t**16 +6.54836e-11*t**17 -34208.1*t**18 -2.72848e-12*t**19 +6466.55*t**20\n",
    "    p_20.append(y)\n",
    "\n",
    "Y = []\n",
    "for t in x:\n",
    "    y = 1/(1+25*t*t)\n",
    "    Y.append(y)\n",
    "plt.figure(figsize=(6,4))\n",
    "plt.plot(x, p_5,\"r\",label=\"n=5\")\n",
    "plt.plot(x, p_10,\"y\",label=\"n=10\")\n",
    "plt.plot(x, p_15,\"g\",label=\"n=15\")\n",
    "plt.plot(x, p_20,\"b\",label=\"n=20\")\n",
    "plt.plot(x, Y,\"k:\",label=\"y\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.xlim(-1,1)\n",
    "plt.ylim(-0.1,1.1)\n",
    "plt.legend()\n",
    "plt.title(\"C\", fontsize=14,x=0.5,y=-0.25)\n",
    "save_picture(plt, \"png\", \"C\")\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "553664ca",
   "metadata": {},
   "source": [
    "# D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "369698e2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "X = np.arange(0, 12, 0.0005)\n",
    "\n",
    "Y = []\n",
    "for x in X:\n",
    "    y = 0 +75*x +7.16191*x**2 -10.0953*x**3 +5.50812*x**4 -1.5383*x**5 +0.243041*x**6 -0.0218757*x**7 +0.00104059*x**8 -2.02236e-05*x**9\n",
    "\n",
    "    Y.append(y)\n",
    "plt.figure(figsize=(6,4))\n",
    "\n",
    "plt.plot(X, Y,\"b\",label=\"y\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.xlim(0,12)\n",
    "plt.ylim(0,1000)\n",
    "plt.legend()\n",
    "plt.title(\"D\", fontsize=14,x=0.5,y=-0.25)\n",
    "save_picture(plt, \"png\", \"D2\")\n",
    "# plt.show()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73e7a071",
   "metadata": {},
   "source": [
    "# E"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "36263ac9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "X = np.arange(0, 30, 0.0005)\n",
    "\n",
    "Y1 = []\n",
    "for x in X:\n",
    "    y1 = 6.67 -43.0127*x +16.2855*x**2 -2.11512*x**3 +0.128281*x**4 -0.00371557*x**5 +4.1477e-05*x**6\n",
    "\n",
    "    Y1.append(y1)\n",
    "plt.figure(figsize=(6,4))\n",
    "\n",
    "plt.plot(X, Y1,\"b\",label=\"y1\")\n",
    "Y2 = []\n",
    "for x in X:\n",
    "    y2 = 6.67 -5.85018*x +2.98227*x**2 -0.424283*x**3 +0.0265858*x**4 -0.000777473*x**5 +8.6768e-06*x**6\n",
    "\n",
    "    Y2.append(y2)\n",
    "plt.plot(X, Y2,\"r\",label=\"y2\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.xlim(0,30)\n",
    "plt.ylim(-40,50)\n",
    "plt.legend()\n",
    "plt.title(\"E\", fontsize=14,x=0.5,y=-0.25)\n",
    "save_picture(plt, \"png\", \"E\")\n",
    "# plt.show()\n",
    "\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
